Human Gene Count Slashed

jd writes "The estimate for the number of genes in human genetic code has been savagely revised downwards. The new estimate, of between 20,000 to 25,000 genes is marginally less than the 27,000 for the Arabidopsis, a flowering plant in the mustard family. Earlier estimates had placed the number of genes at around 44,000 - or even as high as 100,000. Eric Lander of the Broad Institute in Cambridge, Massachusetts is quoted in the CNN story as saying that the number of genes isn't as crucial as how they are used." Read on for more, below.

jd continues: "This has the potential for making life extremely interesting for genetic engineers, given that both individual genes and interactions between genes must be proportionately more complex, in order to get the same level of complexity out. Half the number of genes equates to twice the information encoded in forms other than discrete physical blocks of code.

There is no mention in the article of a story running in 2002 of genetic therapies unexpectedly causing cancer, although if you now factor in the increased complexity of interactions, it is possible that such side-effects can be better understood and therefore prevented. The new estimates, therefore, are more than just idle curiosity but have the potential for impacting how the science is approached."

Comments

Gene Therapy

[Camel Pilot]

Why are we not directing our massive GNP towards scientific exploration such as studying genetic therapies to cure the rift raft of ailiments that curse mankind instead of fighting petty wars against a minor enemy "aka terrorist".

Let look at that stats:

Terrorist kill ~ 3000 people in 2001 and it becomes a focus of the US nation. While:

Breast cancer kills > 40,000 / year

Prostate cancer kills > 30,000 / year

Diabetes kills > 70,000 / year

The numbers world wide of course are much larger.

Yeah OT I know but these kind of discoveries convince me our priorities are misplaced.

Re:Complexity for smaller?

[Nutty_Irishman]

On the contrary, the complexity now increases. There are many genes that act in completely differen't roles depending on the cell type (nerve, epidermal, etc.). So a common language changes from cell type to cell type-- if one would even call it a common language. There is a large part of Bioinformatics/Computational Biology that deals with trying to determine interaction networks between genes. It's very complex, and difficult to deal with.

With less genes we then expect to have a larger amount of downstream interactions between other genes. It might seem that with less genes then we have less to worry about, but we have already speculated for a long time that gene regulatory networks are complex.

To use an analogy (for all you computer geeks), it's like a programmer trying to read poorly modularized code. When you have no idea what class is doing what, and how they interact with other classes (as every class has multiple roles and talks to multiple other classes) then it is difficult to understand why the program behaves the way it does. If the program had many classes that were well modularized and designed with very distinct roles, then it would be easier to understand why things work the way they do.

With less genes and increased complexity we have an even more difficult task. It also highlights some of the reasons on why microarray analysis has not done what we expected it to do. Increasing the complexity and dependency between genes means that we probably are going to take a longer time understanding and extrapolating information from all these networks (which means more job security for me :) ).